Python Data Visualization Transcripts
Chapter: Visualization Concepts
Lecture: Working with data
0:00 We've talked about data visualization quite a bit but I don't want to lose sight of
0:05 the fact that a lot of data visualization should really be a part of working with
0:10 your data. And I thought this quote from Mike Bostok really drove that home.
0:14 I want to give one specific example of tidy data versus wide data to hammer this concept home. When we talk about tidy data,
0:24 I mean data in the example that is one line has all the complete information. It's like a record in a database.
0:31 So in this case for the amazon sales data we have the name of the book
0:36 the author and the user rating and some other information by year we can transform that data into a wide data set using the pivot table function.
0:45 So here we have the fiction and nonfiction reviews by year in the wide data format
0:50 My point with all of this is that when we're doing data visualization,
0:55 you need to be prepared and comfortable using tools like groupby, pivot table, or melt
1:01 to get the data transformed in a way that is most effective for the visualization tool.